STATISTICAL ANALYSIS AND COMPUTATIONAL MODELING CORE PROJECT SUMMARY The Statistical Analysis and Computational Modeling Core is operated by the Division of Nonhuman Primate Systems Biology to provide the resources needed for the processing, management, and analysis of high- throughput data. The computational infrastructure and analytical capabilities provided by the Core are unmatched among the National Primate Research Centers and can be accessed by external investigators through collaboration with Division scientists or directly through the Core using a fee-for-service mechanism. The overall goal of the Core is to help investigators better understand and exploit the information obtained from nonhuman primate models. To do so, it is essential to maintain, plan, and grow the Core?s computational infrastructure to meet the demand of cutting edge technologies. The Specific Aims of the Core are: 1) Provide the IT infrastructure and laboratory information management system for high-throughput data management and analysis. Considering the rapid advances in high-throughput technologies (especially deep sequencing technologies), the Core supports the need for a large computational infrastructure with adequate IT support and it provides a laboratory information management system for efficient project and data management. The Core is constantly improving existing infrastructure, including integration with the WaNPRC IT system and the exploration of hybrid models of combining in-house computational infrastructure with the latest commercial cloud computing. 2) Provide study design, quality control, and primary processing of high-throughput data. After investigators consult with Core personnel on study design, technological choices, and analytical options, the Core employs a standardized data processing pipeline that includes extensive quality control of raw high- throughput datasets, read alignment, abundance quantification and normalization, differential expression, and functional enrichment analysis. Evaluation of emerging computational methods and software is ongoing; as needed current computational pipelines are updated or new ones are developed. 3) Provide advanced analysis of high-throughput multidimensional data. Beyond standard practices outlined in Aim 2 above, Core personnel advise investigators on practical options for advanced data mining. Depending on the study, various strategies can be employed such as integration with additional datasets, network analysis, noncoding RNA function prediction, expression quantitative trait loci analysis, digital cell quantification, time series analysis, target and drug prediction, and association of omics signatures with phenotypic outcomes. All new analytical capabilities developed by the Division are made available through this Core.